Difference between revisions of "TDSM 11.3"
From The Data Science Design Manual Wikia
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| − | Regularization is a technique used in an attempt to solve the overfitting problem in statistical models. (from | + | Regularization is a technique used in an attempt to solve the overfitting problem in statistical models. (from Wikipedia) |
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| + | Textbook page 286: regularization is the trick of adding secondary terms to the objective function to favor models that keep coefficient small. | ||
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| + | Edit: It punishes larger coefficients | ||
Latest revision as of 00:05, 13 December 2017
Regularization is a technique used in an attempt to solve the overfitting problem in statistical models. (from Wikipedia)
Textbook page 286: regularization is the trick of adding secondary terms to the objective function to favor models that keep coefficient small.
Edit: It punishes larger coefficients
